Many practitioners in the field of data governance often find it challenging to gain support from senior leaders for the implementation of a data governance program. This difficulty stems, in part, from the struggle of non-data governance business leaders to visualize the application of data governance within their functions. A strategic approach to overcoming this hurdle involves initially concentrating on integrating data governance into data-related projects and subsequently extending its influence across the broader organizational framework. The rationale behind this strategy lies in the fact that projects have well-defined scopes, providing tangible contexts for business leaders to apply principles and capabilities of data governance. Consequently, data governance transitions from a theoretical priority to a series of attainable steps that contribute tangible business value.

Throughout my 17-year tenure at Thermo Fisher Scientific, I have effectively implemented data governance capabilities, leading to accelerated revenue, reduced risks, and increased productivity. Our recent focus has been on empowering employees to apply data governance principles to some of our most significant projects. In this presentation, we will explore:

• Methods for integrating data governance into waterfall or scaled agile project management frameworks.
• Initial steps to kickstart the implementation of data governance.
• Strategies for enabling non-data governance professionals to drive successful data governance outcomes.
• The transition from a project-centric data governance mindset to a domain-based data governance perspective.

Speaker: John Moran

John Moran leads the Data Governance Enablement team at Thermo Fisher Scientific, headquartered in Waltham, Massachusetts, with more than 100,000 employees operating in over 150 countries. The Data Governance Enablement team is a center of excellence that provides tools and methodologies that enable the business to drive improvements to their data and processes so that they can protect and trust their data, improve their productivity, and make better decisions to deliver on the expectations of both internal and external customers.

In his 17 years at Thermo Fisher, John had held many roles in process improvement and data governance, including over 10 years leading a 70+ member global Product Data Management organization that was responsible for maintaining the data on close to one million products and supported over 20 acquisitions and product portfolio integrations.

Speaker: Donny Bronson

With a profound passion for data integrity and a comprehensive understanding of the strategic importance of effective data management, Donny Bronson is a seasoned Data Governance Professional with extensive experience in the field. Employed at Thermo Fisher Scientific since 2000, Donny brings a wealth of diverse experience spanning various domains including Manufacturing, Research and Development, Operations Integrations, ERP Implementation, and Product Data/Lifecycle Management. Currently in IT, Donny’s focus is on Data Governance Enablement, leveraging his extensive background to drive data excellence across the organization.

Speaker: Julie Giese

Julie Giese leads the Data Catalog and Data Quality team within the Data Governance Enablement team at Thermo Fisher Scientific, headquartered in Waltham, Massachusetts, with more than 100,000 employees operating in over 150 countries. The Data Governance Enablement team is a center of excellence that provides tools and methodologies that enable the business to drive improvements to their data and processes so that they can protect and trust their data, improve their productivity, and make better decisions to deliver on the expectations of both internal and external customers.

During Julie’s 15 years at Thermo Fisher, she has held various roles in Finance, IT, and now Data Governance, from implementing and managing global applications with large complex data sets to her current role managing an enterprise wide data catalog and democratizing data quality.